Dataset Information

Dynamic landscape and evolution of m6A methylation in human.

ABSTRACT: m6A is a prevalent internal modification in mRNAs and has been linked to the diverse effects on mRNA fate. To explore the landscape and evolution of human m6A, we generated 27 m6A methylomes across major adult tissues. These data reveal dynamic m6A methylation across tissue types, uncover both broadly or tissue-specifically methylated sites, and identify an unexpected enrichment of m6A methylation at non-canonical cleavage sites. A comparison of fetal and adult m6A methylomes reveals that m6A preferentially occupies CDS regions in fetal tissues. Moreover, the m6A sub-motifs vary between fetal and adult tissues or across tissue types. From the evolutionary perspective, we uncover that the selection pressure on m6A sites varies and depends on their genic locations. Unexpectedly, we found that ?40% of the 3'UTR m6A sites are under negative selection, which is higher than the evolutionary constraint on miRNA binding sites, and much higher than that on A-to-I RNA modification. Moreover, the recently gained m6A sites in human populations are clearly under positive selection and associated with traits or diseases. Our work provides a resource of human m6A profile for future studies of m6A functions, and suggests a role of m6A modification in human evolutionary adaptation and disease susceptibility.

SUBMITTER: Zhang H

PROVIDER: S-EPMC7293016 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dynamic landscape and evolution of m6A methylation in human.

Zhang Hui H Shi Xinrui X Huang Tao T Zhao Xueni X Chen Wanying W Gu Nannan N Zhang Rui R

Nucleic acids research 20200601 11

m6A is a prevalent internal modification in mRNAs and has been linked to the diverse effects on mRNA fate. To explore the landscape and evolution of human m6A, we generated 27 m6A methylomes across major adult tissues. These data reveal dynamic m6A methylation across tissue types, uncover both broadly or tissue-specifically methylated sites, and identify an unexpected enrichment of m6A methylation at non-canonical cleavage sites. A comparison of fetal and adult m6A methylomes reveals that m6A pr ...[more]

PMID: 32406913

Similar Datasets

Project description:ObjectiveEpigenetic aberration plays an important role in the development and progression of hepatocellular carcinoma (HCC). However, the alteration of RNA N6-methyladenosine (m6A) modifications and its role in HCC progression remain unclear. We therefore aimed to provide evidence using bioinformatics analysis.MethodsWe comprehensively analyzed the m6A regulator modification patterns of 605 HCC samples and correlated them with metabolic alteration characteristics. We elucidated 390 gene-based m6A-related signatures and defined an m6Ascore to quantify m6A modifications. We then assessed their values for predicting prognoses and therapeutic responses in HCC patients.ResultsWe identified 3 distinct m6A modification patterns in HCC, and each pattern had distinct metabolic characteristics. The evaluation of m6A modification patterns using m6Ascores could predict the prognoses, tumor stages, and responses to sorafenib treatments of HCC patients. A nomogram based on m6Ascores showed high accuracy in predicting the overall survival of patients. The area under the receiver operating characteristic curve of predictions of 1, 3, and 5-year overall survivals were 0.71, 0.69, and 0.70 in the training cohort, and in the test cohort it was 0.74, 0.75, and 0.71, respectively. M6Acluster C1, which corresponded to hypoactive mRNA methylation, lower expression of m6A regulators, and a lower m6Ascore, was characterized by metabolic hyperactivity, lower tumor stage, better prognosis, and lower response to sorafenib treatment. In contrast, m6Acluster C3 was distinct in its hyperactive mRNA methylations, higher expression of m6A regulators, and higher m6Ascores, and was characterized by hypoactive metabolism, advanced tumor stage, poorer prognosis, and a better response to sorafenib. The m6Acluster, C2, was intermediate between C1 and C3.ConclusionsHCCs harbored distinct m6A regulator modification patterns that contributed to the metabolic heterogeneity and diversity of HCC. Development of m6A gene signatures and the m6Ascore provides a more comprehensive understanding of m6A modifications in HCC, and helps predict the prognosis and treatment response.

Project description:MOTIVATION:As the most abundant mammalian mRNA methylation, N6-methyladenosine (m6A) exists in >25% of human mRNAs and is involved in regulating many different aspects of mRNA metabolism, stem cell differentiation and diseases like cancer. However, our current knowledge about dynamic changes of m6A levels and how the change of m6A levels for a specific gene can play a role in certain biological processes like stem cell differentiation and diseases like cancer is largely elusive. RESULTS:To address this, we propose in this paper FunDMDeep-m6A a novel pipeline for identifying context-specific (e.g. disease versus normal, differentiated cells versus stem cells or gene knockdown cells versus wild-type cells) m6A-mediated functional genes. FunDMDeep-m6A includes, at the first step, DMDeep-m6A a novel method based on a deep learning model and a statistical test for identifying differential m6A methylation (DmM) sites from MeRIP-Seq data at a single-base resolution. FunDMDeep-m6A then identifies and prioritizes functional DmM genes (FDmMGenes) by combing the DmM genes (DmMGenes) with differential expression analysis using a network-based method. This proposed network method includes a novel m6A-signaling bridge (MSB) score to quantify the functional significance of DmMGenes by assessing functional interaction of DmMGenes with their signaling pathways using a heat diffusion process in protein-protein interaction (PPI) networks. The test results on 4 context-specific MeRIP-Seq datasets showed that FunDMDeep-m6A can identify more context-specific and functionally significant FDmMGenes than m6A-Driver. The functional enrichment analysis of these genes revealed that m6A targets key genes of many important context-related biological processes including embryonic development, stem cell differentiation, transcription, translation, cell death, cell proliferation and cancer-related pathways. These results demonstrate the power of FunDMDeep-m6A for elucidating m6A regulatory functions and its roles in biological processes and diseases. AVAILABILITY AND IMPLEMENTATION:The R-package for DMDeep-m6A is freely available from https://github.com/NWPU-903PR/DMDeepm6A1.0. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

Dataset Information

Dynamic landscape and evolution of m6A methylation in human.

Publications

Dynamic landscape and evolution of m6A methylation in human.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets